Medical imaging systems may use nuclear materials, called radiopharmaceuticals, for the imaging. One such imaging system is single photon emission computed tomography, abbreviated as SPECT. Typical types of imaging may include single photon emission computed tomography or SPECT, Cardiac SPECT and Cardiac Gated SPECT, as well as others. Other techniques may include general nuclear medicine, which includes whole body and organ-specific planar imaging techniques, positron emission tomography (“PET”) as well as magnetic resonance imaging.
Imaging systems of this type may be dependent on many variables. Patient motion during all types of Nuclear Medicine Imaging studies may cause misregistration of acquired projection data. The motion may result in the addition of artifacts to the reconstructed images.
For example, artifacts created by patient motion are a function of the time, degree, and type of motion as well as the number of camera detectors. These artifacts can cause misdiagnosis, due to the similarity of such defects to actual pathological conditions.
For example, patient motion induced-artifacts in 99mTc (metastable Technetium-99)-based myocardial perfusion SPECT images, may form a potential source of false-positive findings for coronary artery disease. However, analogous image distortion may occur in other medical imaging techniques, such as Positron Emission Tomography (PET), X-ray Computed Tomography (CT) and non-Cardiac Nuclear Medicine.
Post acquisition software motion correction has been used to attempt to correct images for patient motion. Cedars-Sinai MOCO is an existing package that decreases motion artifacts on SPECT imaging studies, such as myocardial perfusion SPECT images. MOCO uses a variety of post data acquisition algorithms to compensate the pre-reconstructed data sets for patient motion. MOCO attempts to mathematically shift the center of mass distribution of the post-acquired projections after each frame to compensate for patient motion distortion artifacts.
Software correction methods on two-dimensional projection data after image acquisition, however, have a limited ability to correct for certain kinds of movements: including patient twisting, organ rotation, and vertical slumping which is prevalent with upright patient seating orientation. Post acquisition software motion correction has other drawbacks and deficiencies that affect both diagnostic accuracy, technologist, and patient workflow. Some issues include:
a. The software operates on the motion-integrated data. The acquired projections effectively integrate patient motion for the entire frame scan. The software can only correct for the average position of the organ of interest during each frame. This may result in limited accuracy of the correction, as well as the inability to identify or discard large transient motions that may contaminate the data.
b. Mixed mode motion, such as patient twisting or organ rotation caused by patient respiration, may not be compensated correctly, because the software correction algorithms operate on the projection data as seen by the detectors, instead of the organ of interest directly. This limitation may result in either over- or under-correcting each orthogonal degree of motion in the study.
c. The inability of the software motion correction algorithms to account for, or notify the technologist of, uncorrectable motions during the study may even result in a need to rescan some patients. This in turn, may reduce the capacity of the imaging site to process patients.
d. Because of the inadequacies of present motion correction software, studies are frequently reconstructed both with and without motion correction software. The technologist must frequently analyze and prepare studies both with and without motion correction applied. This allows the physician to decide which method of reconstruction is most realistic and contains the fewest artifacts.
e. In exercise multigated blood-pool imaging, significant degradation of image quality occurs as a result of patient movement under the gamma camera. Motion correction devices using centroid tracking of x-y events emanating from the organ of interest cannot be applied to blood-pool studies, because cardiac contraction rotation masks the correctable patient motion component.